Responsibilities
- Creating interfaces and APIs that give scientists and AI agents visibility into what's happening in the lab in real time
- Building custom AI agents and tooling that automate decisions across the experiment lifecycle, from protocol design to troubleshooting failed results
- Turning proprietary hardware into API-controllable devices that agents and software can operate programmatically
- Designing scheduling systems that coordinate dozens of lab instruments with complex dependency chains
Requirements
- Full-stack production experience
- Product instinct. You've shipped, watched users, iterated, and shipped again
- Comfortable in ambiguity. You start from a goal, not a spec. You scope problems down, decide what to build and what to skip, and write your own plan when none exists
- Builds with AI. You use AI tools heavily, but you have enough experience without them to know what good looks like
- Curious about biology. No background required, but running real experiments in the physical world should excite you
Tech Stack
TypeScript, React, Node, Postgres
Team
Team size: small team. Structure: individual engineers have large impact on what gets built and how
